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​よろず知財コンサルティングのブログ

自律型AIエージェントが科学的発見プロセスを変革

22/3/2026

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自律型AIエージェントが科学的発見のプロセスを根本から変革し、AIは単なる補助ツールを超え、人類の創造性を高める自律的な科学的協働者へと進化を遂げています。
Harmonic社が開発したAristotle Agentは、形式言語を用いた検証により「幻覚」を排除し、未解決の数学的難問を自律的に証明する数学的超知能を実現しました。
オープンソースのGet Physics Done (GPD)は、理論の定式化から実験シミュレーション、論文執筆に至るまでの物理学研究のワークフローを統合的に実行します。
これらのシステムにより、厳密な論理と物理的妥当性を備えた科学的知見が工業的規模で生成され、AIが人類の創造性を高める自律的な科学的協働者へと進化を遂げていることがわかります。
生成AIにこれらの論点について深堀させました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
Meet Aristotle Agent
https://x.com/HarmonicMath/status/2034028065513451594
 
Get Physics Done (GPD)
https://sourceforge.net/projects/get-physics-done-gpd.mirror/
 
 
Autonomous AI Agents Transform the Process of Scientific Discovery
Autonomous AI agents are fundamentally transforming the process of scientific discovery. AI is evolving beyond a mere assistive tool into an autonomous scientific collaborator that enhances human creativity.
The Aristotle Agent, developed by Harmonic, eliminates “hallucinations” through verification using formal languages and achieves mathematical superintelligence capable of autonomously proving unsolved mathematical problems.
The open-source Get Physics Done (GPD) system executes the entire physics research workflow in an integrated manner, from theoretical formulation to experimental simulation and paper writing.
These systems enable the industrial-scale generation of scientific knowledge grounded in rigorous logic and physical validity, demonstrating that AI is evolving into an autonomous scientific partner that amplifies human creativity.
The above issues have been further analyzed using generative AI. However, please note that such AI-based analysis is based solely on publicly available information, does not necessarily reflect actual circumstances, and may contain inaccuracies.
 

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測定方法に基づく構成要件充足性の判断

22/3/2026

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測定方法に基づく構成要件充足性の判断という視点では、昔の苦い経験を思い出します。
平成27年(ネ)10016号「ティシュペーパー」事件です。権利者に厳しすぎる判決という評釈もありましたが、判決後は、出願時の明細書のチェックを厳しくしたことを覚えています。
生成AIにこの判決を評釈させました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
平成28年9月28日判決言渡 同日原本領収 裁判所書記官
平成27年(ネ)第10016号 特許権侵害差止等請求控訴事件
(原審・東京地方裁判所平成24年(ワ)第6547号)判決
https://www.courts.go.jp/assets/hanrei/hanrei-pdf-86166.pdf
 
2016.10.11 侵害訴訟等
平成27年(ネ)10016号「ティシュペーパー」事件
https://unius-pa.com/infringement_lawsuit/4146/
https://www.unius-pa.com/wp/wp-content/uploads/h27_ne_10016.pdf
 
特許権侵害訴訟の近時判例の調査・分析
https://www.jipa.or.jp/kaiin/kikansi/honbun/2017_01_051.pdf
ティシュぺーパー事件(事例2)
 
知財高裁平成27年(ネ)第10016号 特許権侵害差止等請求控訴事件
https://www.nakapat.gr.jp/wp-content/uploads/2019/07/11%E6%96%87%E6%9B%B8.pdf
 
測定方法に基づく構成要件充足性の判断 ―ティシュペーパー事件―
https://www.jipa.or.jp/kaiin/kikansi/honbun/2017_11_1735.pdf
 
数値限定発明の充足論,明確性要件
https://jpaa-patent.info/patent/viewPdf/3011
 
 
Determination of Satisfaction of Claim Requirements Based on Measurement Methods
From the perspective of determining whether claim requirements are satisfied based on measurement methods, I am reminded of a bitter experience from the past. It is the “Tissue Paper” case (Heisei 27 (Ne) No. 10016). Although some commentaries criticized the judgment as being overly harsh on the patentee, I recall that after the decision, we became much more rigorous in reviewing specifications at the time of filing.
I asked generative AI to provide a commentary on this judgment. Please note that the investigation and analysis results generated by AI are based solely on publicly available information and do not necessarily reflect the actual circumstances; they may also contain inaccuracies. Please keep this in mind when referring to them.

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数値限定発明における測定方法と明確性要件

22/3/2026

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特許庁審判部が公表した「審判実務者研究会報告書2025」における事例研究1テーマ1「測定方法と明確性要件」では、以下の3つの論点に沿い、数値限定発明における明確性要件の判断枠組みと実務上の留意点が整理されています。
論点1:測定方法が不明確と判断されないために、明細書に記載しておくべき事項とは
論点2:測定方法を理解する際に、明細書には記載されていないが、考慮されるべき事項とは
論点3:測定方法がどの程度明らかであるといえれば、明確性要件を充足するといえるのか
報告書によれば、その要点は下記のようになります。
まず、測定方法の記載に関しては、明確性要件の判断は請求項の記載のみならず明細書の記載も踏まえて行われることを前提に、当業者が理解可能な程度で測定方法や測定条件を明示することの重要性が確認された。特に数値限定発明においては、測定方法の不明確さが権利範囲の不安定化を招くため、可能な限り具体的に記載することが望ましいとされる。一方で、測定方法にノウハウが含まれる場合など、過度な詳細記載が出願人に不利益をもたらす可能性についても指摘されており、記載の程度には一定のバランスが求められる。
次に、明細書に記載されていない事項の取扱いについては、出願時の技術常識や業界標準、規格等が補完的に考慮され得ることが示された。すなわち、明確性の判断は明細書の文言に限定されるものではなく、当業者の知識を前提として測定方法が理解可能であるかという観点から行われる。ただし、これらの技術常識に依拠するためには適切な立証が必要であり、単なる主張のみでは足りない点には留意が必要である。
さらに、測定方法の明確性の程度については、測定方法が一義的に定まる場合には問題なく明確といえる一方、複数の合理的な測定方法が想定される場合には、それらの方法によって得られる測定値が一定範囲に収まることが求められると整理された。また、測定値のばらつきについては、不可避的な測定誤差と測定方法の不確定性に起因するばらつきとを区別すべきであり、後者により技術的範囲の外縁が不明確となる場合には問題が生じ得るとされる。
生成AIにこれらの論点について深堀させました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
事例研究1 テーマ1(特許機械1)
測定方法と明確性要件
https://www.jpo.go.jp/resources/shingikai/kenkyukai/sinposei_kentoukai/document/2025_houkokusyo/01_machinery1.pdf
 
 
Measurement Methods and Clarity Requirements in Numerical Limitation Inventions
In Case Study 1, Theme 1 (“Measurement Methods and Clarity Requirements”) of the Trial and Appeal Practitioner Study Group Report 2025 published by the Trial and Appeal Department of the Japan Patent Office (JPO), the framework for assessing the clarity requirement in numerical limitation inventions, as well as key practical considerations, are organized around the following three issues :
  • Issue 1: What should be described in the specification to avoid a finding that the measurement method is unclear?
  • Issue 2: What information, though not described in the specification, should be considered when understanding the measurement method?
  • Issue 3: To what extent must a measurement method be clear in order to satisfy the clarity requirement?
According to the report, the key points can be summarized as follows:
First, regarding the description of measurement methods, it is premised that the clarity requirement is assessed not only based on the claims but also in light of the specification. It was reaffirmed that it is important to explicitly describe the measurement methods and conditions to an extent understandable by a person skilled in the art. Particularly in numerical limitation inventions, ambiguity in measurement methods may lead to instability in the scope of rights; therefore, it is desirable to describe them as concretely as possible. On the other hand, it was also pointed out that, where the measurement method involves know-how, excessively detailed disclosure may disadvantage the applicant, and thus an appropriate balance in the level of description is required .
Next, with respect to matters not described in the specification, it was indicated that common general knowledge at the time of filing, industry standards, and technical norms may be taken into account in a supplementary manner. In other words, the determination of clarity is not limited to the literal wording of the specification but is made from the perspective of whether a person skilled in the art can understand the measurement method. However, reliance on such common general knowledge requires appropriate substantiation, and mere assertions are insufficient .
Furthermore, regarding the degree of clarity required for measurement methods, it was organized that where the measurement method is uniquely determined, it can be regarded as clear without issue. In contrast, where multiple reasonable measurement methods may be envisaged, it is required that the measurement values obtained by those methods fall within a certain range. In addition, variability in measured values should be distinguished between unavoidable measurement error and variability arising from uncertainty in the measurement method itself; if the latter results in ambiguity in the outer boundary of the technical scope, problems may arise .
The above issues have been further analyzed using generative AI. However, please note that such AI-based analysis is based solely on publicly available information, does not necessarily reflect actual circumstances, and may contain inaccuracies.

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「知的財産推進計画2026」の策定に向けた意見募集の結果

21/3/2026

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知的財産推進計画2026は、2026年6月の知的財産戦略本部決定に向けて策定が進行中で、AI時代の知財制度構築、コンテンツ産業のグローバル展開、海賊版被害の急増への対応が三大焦点となっています。
2025年12月1日から2026年1月7日までのパブリックコメントには多数の意見が寄せられ、とくにAI学習データの透明性確保、robots.txtの法的義務化、クリエイターへの対価還元が重要論点として浮上しました。
生成AIに、『「知的財産推進計画2026」の策定に向けた意見募集の結果』を深掘りさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
「知的財産推進計画2026」の策定に向けた意見募集の結果について
https://www.cas.go.jp/jp/seisakukaigi/titeki2/chitekizaisan2026/index.html
 
 
Results of the Public Consultation Toward the Formulation of the “Intellectual Property Strategic Program 2026”
The Intellectual Property Strategic Program 2026 is currently being formulated for a decision by the Intellectual Property Strategy Headquarters in June 2026. The three major focal points are: the development of an intellectual property system suited to the AI era, the global expansion of the content industry, and responses to the rapid increase in damage caused by piracy.
A large number of comments were submitted during the public consultation period from December 1, 2025 to January 7, 2026. In particular, key issues that emerged included ensuring transparency of AI training data, the legal obligation of robots.txt, and fair compensation for creators.
I asked generative AI to conduct an in-depth analysis of the “Results of the Public Consultation Toward the Formulation of the Intellectual Property Strategic Program 2026.” Please note that the research and analysis conducted by generative AI are based solely on publicly available information and may not necessarily reflect the actual situation, and may contain inaccuracies.
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審判実務者研究会報告書2025

21/3/2026

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2026年3月19日、特許庁審判部から「審判実務者研究会報告書2025」が公表されました。
今年度の研究会では、特許4分野(機械1、機械2、化学、電気)及び商標分野において、それぞれ①一般的な論点(測定方法と明確性要件、技術常識等を踏まえた進歩性判断、サポート要件、クレームで用いられている用語の解釈と明確化、商標法4条1項7号に係る後発的無効理由(商標法46条1項6号))と②個別事例(審判実務上重要と思われる裁判例及びその対象となった審決)について検討されています。
この報告書に関して、生成AIに紹介してもらいました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
審判実務者研究会報告書2025の公表について
令和8年3月19日
https://www.jpo.go.jp/system/trial_appeal/info-sinposei_kentoukai.html
 
特許庁審判部
 
特許庁審判部では、平成18年度(2006年度)から、産業界、弁理士、弁護士、裁判官(オブザーバー参加)及び審判官という各々立場の異なる審判実務関係者が一堂に会して審決や判決についての研究を行う「審判実務者研究会」(当初は「進歩性検討会」)を開催し、その成果を公表するなどの取組を行っています。
 
今年度の研究会では、特許4分野(機械1、機械2、化学、電気)及び商標分野において、それぞれ①一般的な論点(測定方法と明確性要件、技術常識等を踏まえた進歩性判断、サポート要件、クレームで用いられている用語の解釈と明確化、商標法4条1項7号に係る後発的無効理由(商標法46条1項6号))と②個別事例(審判実務上重要と思われる裁判例及びその対象となった審決)について検討しました。今年度は、分野別の会合のほとんどを対面形式の会議で行い(一部はハイブリッド会議)、活発な議論が行われました。
 
 
Trial Practice Study Group Report 2025
On March 19, 2026, the Trial and Appeal Department of the Japan Patent Office (JPO) released the “Trial Practice Study Group Report 2025.”
In this year’s study group, discussions were conducted in four patent fields (Mechanical I, Mechanical II, Chemistry, and Electrical) as well as the trademark field, focusing on:
(1) general issues—such as measurement methods and clarity requirements, inventive step assessment based on common general knowledge, support requirements, interpretation and clarification of terms used in claims, and post-registration grounds for invalidation under Article 4(1)(vii) of the Trademark Act (Article 46(1)(vi) of the same Act); and
(2) specific cases—namely court decisions considered important for trial practice and the corresponding appeal/trial decisions.
I asked generative AI to provide an overview of this report. Please note that the analysis and findings generated by AI are based solely on publicly available information and may not necessarily reflect the actual situation; they may also contain inaccuracies.

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ソフトバンクGの大量特許出願が日本企業の知財戦略に与える影響

20/3/2026

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ソフトバンクグループは、2023年9月・2024年7〜8月・2025年12月の三つの時期に集中的な大量特許出願を行ってきたと考えられています。
このソフトバンクグループの大量特許出願が日本企業の知財戦略に与える影響について生成AIに深掘りさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
The Impact of SoftBank Group’s Large-Scale Patent Filings on the IP Strategies of Japanese Companies
SoftBank Group is believed to have conducted concentrated waves of large-scale patent filings during three periods: September 2023, July–August 2024, and December 2025.
I used generative AI to conduct an in-depth analysis of how these large-scale patent filings by SoftBank Group may impact the intellectual property strategies of Japanese companies. Please note that the analysis and findings generated by AI are based solely on publicly available information, and may not fully reflect actual conditions; they may also contain inaccuracies.
 

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ソフトバンクグループの大量特許出願

20/3/2026

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ソフトバンクグループは、2023年9月・2024年7〜8月・2025年12月の三つの時期に集中的な大量特許出願を行ってきたと考えられています。
第1波・第2波については既に公開公報として確認され、2025年の出願公開件数ランキングで断トツの第1位(約1万400件)を記録しました。
第3波とされる2025年12月の出願については、同月の日本全体の特許出願件数が前年同月比約2.7倍の82,188件に達していて、その多くがソフトバンクグループによるものである可能性が強く推測されています。
このソフトバンクグループの特許出願について生成AIに深掘りさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
2024年7月・8月の大量出願と2025年12月の大量出願
27/2/2026
 
ソフトバンクの大量特許出願が4月に約1万件公開
​
12/4/2025
 
ソフトバンクグループの成長戦略における知的財産部門の貢献
12/1/2025
 
 
Large-Scale Patent Filings by SoftBank Group
It is believed that SoftBank Group has conducted concentrated waves of large-scale patent filings during three periods: September 2023, July–August 2024, and December 2025.
The first and second waves have already been confirmed through published patent gazettes, and the company ranked overwhelmingly first in the number of published applications in 2025, with approximately 10,400 filings.
As for the third wave, which is considered to have occurred in December 2025, the total number of patent applications in Japan that month reached 82,188—about 2.7 times higher than the same month of the previous year. It is strongly presumed that a significant portion of these filings was made by SoftBank Group.
WIasked generative AI to conduct a multifaceted, in-depth analysis of these patent filings by SoftBank Group. Please note that the investigation and analysis conducted by generative AI are based solely on publicly available information and may not necessarily reflect the actual situation; they may also contain inaccuracies.

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米中AI技術覇権争いが日本企業の知財戦略に及ぼす影響

20/3/2026

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米中間のAI技術覇権争いは、米国が輸出規制や投資審査を通じて技術封鎖を強める一方、中国は特許の量とデータ統制で独自のエコシステム構築を急いでおり、世界は二極化の様相を呈しています。
生成AIに、米中のAI技術覇権争いが日本企業の知的財産戦略に及ぼす影響を多角的に分析させました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
The Impact of the U.S.–China AI Technology Hegemony Competition on the Intellectual Property Strategies of Japanese Companies
The competition for AI technological supremacy between the United States and China is intensifying: the U.S. is strengthening technological containment through export controls and investment screening, while China is accelerating the construction of its own ecosystem through the volume of patents and strict data governance. As a result, the world is increasingly exhibiting signs of bifurcation.
I asked a generative AI system to conduct a multifaceted analysis of how this U.S.–China AI technology rivalry may affect the intellectual property strategies of Japanese companies. Please note that the investigation and analysis generated by AI are based solely on publicly available information and may not necessarily reflect actual conditions; they may also contain inaccuracies.

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人工知能(AI)分野における米中の覇権争い

20/3/2026

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人工知能(AI)分野における米中の覇権争いは、米国が民間主導の革新と圧倒的な投資力で先端モデルを牽引する一方、中国は国家戦略「AI+」や第15次5カ年計画を軸に、社会実装や知的財産の量的な面で猛追している状況です。
この状況を生成AIに深掘りさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
The U.S.–China Rivalry for Supremacy in Artificial Intelligence (AI)
The competition between the United States and China for dominance in the field of artificial intelligence (AI) is characterized by a contrast in approaches. The United States is leading the development of advanced models through private-sector-driven innovation and overwhelming investment capacity. Meanwhile, China is rapidly catching up by leveraging national strategies such as “AI+” and its 15th Five-Year Plan, focusing on large-scale social implementation and the quantitative expansion of intellectual property.
This situation has been further analyzed in depth using generative AI. Please note that the analysis and findings generated by AI are based solely on publicly available information and may not necessarily reflect the full reality; they may also contain inaccuracies.

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令和7年(行ケ)第10003号「ベッド」 進歩性(一致点の認定)

19/3/2026

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令和7年( 行ケ)第10003号判決は、考案の名称を「ベッド」とする実用新案につき、新規性及び進歩性がないとした審決について、審決が引用例との対比において一致点の認定を誤ったとして、審決を取り消した事例です。
今回の審決の認定は、引用例との対比において一致点を過度に広く認定することで相違点を消去する手法の典型例ともいえるかもしれません。知財高裁がこれを厳格に是正したことは、クレーム解釈の適正化という観点から、今後の審判、審査に影響が出てくるかもしれません。
この判決について、生成AIに評釈させました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
令和7年(行ケ)第10003号「ベッド」 判決要旨及び判決全文
https://www.courts.go.jp/hanrei/94884/detail8/index.html
 
2026.02.20知財判決ダイジェスト
実用新案 令和7年(行ケ)第10003号「ベッド」(知的財産高等裁判所 令和7年9月30日)
https://www.soei.com/%E7%89%B9%E8%A8%B1%E3%80%80%E4%BB%A4%E5%92%8C%EF%BC%97%E5%B9%B4%EF%BC%88%E8%A1%8C%E3%82%B1%EF%BC%89%E7%AC%AC%EF%BC%91%EF%BC%90%EF%BC%90%EF%BC%90%EF%BC%93%E5%8F%B7%E3%80%8C%E3%83%99%E3%83%83%E3%83%89/
 
2026.2.17 審決取消訴訟等
令和7年(行ケ)第10003号「ベッド」事件
https://unius-pa.com/decision_cancellation/10566/
https://unius-pa.com/wp/wp-content/uploads/2026/02/R7_gyoke_10003.pdf
 
2026.01.06
ベッド 審決取消請求事件
https://www.meisei.gr.jp/report/%E3%83%99%E3%83%83%E3%83%89-%E5%AF%A9%E6%B1%BA%E5%8F%96%E6%B6%88%E8%AB%8B%E6%B1%82%E4%BA%8B%E4%BB%B6/
 
Reiwa 7 (Gyo-Ke) No. 10003 “Bed” — Inventive Step (Error in Identifying Points of Agreement)
The judgment in Reiwa 7 (Gyo-Ke) No. 10003 concerns a utility model titled “Bed.” It is a case in which the court set aside a JPO decision that had found the claimed invention to lack novelty and inventive step, on the grounds that the JPO had erred in identifying the points of agreement with the cited reference in its comparative analysis.
The JPO’s reasoning in this case may be regarded as a typical example of a method in which differences are effectively eliminated by defining the points of agreement with the cited reference overly broadly. The Intellectual Property High Court’s strict correction of this approach may influence future trials and examinations, particularly from the perspective of ensuring proper claim interpretation.
A commentary on this judgment was generated using AI. Please note that the AI-based analysis and findings are derived solely from publicly available information and may not necessarily reflect the actual circumstances; they may also contain inaccuracies.

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2025年度プライム市場知財・無形資産ガバナンス調査報告書

18/3/2026

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2026年3月6日に行われた「知財投資・活用戦略の有効な開示及びガバナンスに関する検討会」(第28回)において、一般社団法人 知財・無形資産ガバナンス協会が「プライム市場時価総額上位700社に対する知財・無形資産ガバナンスの実践状況調査報告(2025年度)」を報告しました。(私も本調査に協力しました。)
日本のプライム市場上場企業における知財・無形資産ガバナンスの浸透度と情報開示の実態を多角的に分析した調査報告書です。多くの企業が制度上の形式的な遵守にとどまっている現状、特に、投資家が重視するアウトカム志向の指標(KPI)の欠如や、業種・時価総額による開示水準の格差といった構造的課題が浮き彫りになっています。
一方で、経営戦略と知財戦略を高度に融合させている先進事例のレベルは年々向上しています。本年度は、⽇清オイリオグループ株式会社(2602)、味の素株式会社(2802)、三井⾦属株式会社(5706)、株式会社デンソー(6902)、東京エレクトロン(8035)、住友商事株式会社(8053)を好事例として紹介しています。
この報告書を生成AIに深掘りさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
プライム市場時価総額上位700社に対する知財・無形資産ガバナンスの実践状況調査報告(2025年度)
https://www.cas.go.jp/jp/seisakukaigi/titeki2/tyousakai/tousi_kentokai/dai28/shiryo4.pdf
 
 
FY2025 Report on Intellectual Property and Intangible Asset Governance in the Prime Market
At the 28th meeting of the “Study Group on Effective Disclosure and Governance of IP Investment and Utilization Strategies,” held on March 6, 2026, the Japan Intellectual Property and Intangible Asset Governance Association presented its “Survey Report on the Implementation Status of IP and Intangible Asset Governance among the Top 700 Prime Market Companies by Market Capitalization (FY2025).” (I also contributed to this survey.)
This report provides a multifaceted analysis of the level of penetration of IP and intangible asset governance and the actual state of information disclosure among companies listed on Japan’s Prime Market. It reveals structural challenges, including the fact that many companies remain at the level of formal compliance with institutional requirements, as well as the lack of outcome-oriented indicators (KPIs) valued by investors and disparities in disclosure levels depending on industry and market capitalization.
At the same time, the level of advanced cases that successfully integrate management strategy with IP strategy continues to improve year by year. This year’s report highlights exemplary cases such as Nisshin OilliO Group, Ajinomoto Co., Mitsui Mining & Smelting, DENSO Corporation, Tokyo Electron, and Sumitomo Corporation.
I conducted a deeper analysis of this report using generative AI. Please note that the AI-generated research and analysis are based solely on publicly available information and may not fully reflect actual conditions; they may also contain inaccuracies.

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「Perplexity Computer」「Personal Computer」の知財業務への影響

16/3/2026

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Perplexityは2026年2月にPerplexity Computer(19モデルを統合したマルチエージェントクラウド基盤)、3月11日の開発者会議「Ask 2026」にてPersonal Computer(Mac miniをローカル拠点とする24時間稼働型エージェント)を相次いで発表しました。両製品は、AIを「回答生成ツール」から「ワークフロー実行エンジン」へと転換させる設計思想を共有しており、特許調査・明細書作成・中間応答・ポートフォリオ管理を含む知財業務全般に対して、機会と脅威の双方から多大な影響を与える可能性があります。
「Perplexity Computer」と「Personal Computer」の具体的な影響を生成AIに多角的に分析させました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
The Impact of “Perplexity Computer” and “Personal Computer” on Intellectual Property Operations
In February 2026, Perplexity announced Perplexity Computer, a multi-agent cloud platform that orchestrates 19 AI models. Subsequently, at its developer conference “Ask 2026” on March 11, the company unveiled Personal Computer, a continuously operating AI agent system that uses a Mac mini as a local hub.
Both products share a design philosophy that transforms AI from a “response-generation tool” into a “workflow execution engine.” As a result, they have the potential to exert significant influence—both as an opportunity and as a threat—across the entire spectrum of intellectual property operations, including patent searches, specification drafting, office action responses, and portfolio management.
I asked generative AI to conduct a multifaceted analysis of the specific impacts of Perplexity Computer and Personal Computer.
Please note that the investigation and analysis produced by generative AI are based solely on publicly available information and may not necessarily reflect the actual situation; they may also contain inaccuracies. Readers are advised to review the content with this understanding in mind.

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「Perplexity Computer」、そして「Personal Computer」

16/3/2026

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Perplexity AIは2026年2月25日、「Perplexity Computer」を発表しました。Perplexity Computerは、19〜20個のAIモデルをオーケストレーションしてワークフロー全体を自律実行するクラウドエージェント基盤で、ユーザーが期待する成果を入力するとシステムがタスクとサブタスクに分解し、複数のサブエージェントを非同期・並列で生成して成果物を生成します。
さらに、2026年3月11日には「Personal Computer」を発表しました。Personal Computerは、クラウドベースのComputerをローカルマシンと融合させたハイブリッドアーキテクチャで、Mac miniに常時稼働させるソフトウェアとして動作します。
Perplexity AIは、創業からわずか3年でAI検索エンジンの枠を超え、マルチモデル・ワークフロー自動化基盤として企業ITスタックに正面から挑戦するフェーズへ移行しています。
このPerplexityの動きを生成AIに深掘りさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
Perplexityが「Personal Computer」を発表──AI検索エンジンが"24時間働くデジタル社員"へと進化した全貌
https://meta-heroes.co.jp/member-blog/perplexity-personal-computer-ask-2026
 
Perplexity、マルチモデル統合型AI基盤「Perplexity Computer」を発表
19のAIモデルをオーケストレーションし、ワークフロー全体を自律実行
https://prtimes.jp/main/html/rd/p/000000020.000157647.html
 
 
“Perplexity Computer” and “Personal Computer”
On February 25, 2026, Perplexity AI announced “Perplexity Computer.”
Perplexity Computer is a cloud-based agent platform that orchestrates 19–20 AI models to autonomously execute entire workflows. When a user inputs the desired outcome, the system decomposes the task into multiple tasks and subtasks, generates several sub-agents asynchronously and in parallel, and produces the final deliverables.
Furthermore, on March 11, 2026, the company announced “Personal Computer.”
Personal Computer adopts a hybrid architecture that combines the cloud-based Computer with a local machine. It operates as software that runs continuously on a Mac mini.
In just three years since its founding, Perplexity AI has moved beyond the framework of an AI search engine and entered a phase where it is directly challenging the enterprise IT stack as a multi-model workflow automation platform.
I asked generative AI to conduct a deeper analysis of these developments at Perplexity. Please note that the investigation and analysis generated by AI are based solely on publicly available information and may not necessarily reflect the actual situation; inaccuracies may also be included.

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「Claude Cowork」の知財業務における活用法

15/3/2026

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2026年1月にMac版が、同年2月にWindows版がリリースされたAnthropic「Claude Cowork」は、自然言語による指示でPC上のファイル操作やブラウザ操作を自律的に実行するAIエージェント機能で、非エンジニアでも複雑な業務を自動化できるツールとして注目を集めています。
Claude Coworkは特に「精読・分析・慎重な文書作成」が求められる業務領域で強みを発揮し、アイデア出しや汎用的なタスク処理に強いChatGPTなどとは異なり、契約書レビューや規制対応といった、正確性と保守的な判断が重視される法務・知財業務との親和性が極めて高いと評価されています。
知的財産業務においては、特許ポートフォリオの整理・分析、競合他社の特許動向調査、ライセンス契約書のレビュー、弁理士など専門家とのコミュニケーション支援まで、多岐にわたる活用が可能とされています。ただし、ローカルファイルにアクセスする特性上、機密情報の取り扱いには十分な注意が必要です。
「Claude Cowork」について、知財業務における活用法を生成AIに深掘りさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
Applications of “Claude Cowork” in Intellectual Property Operations
Claude Cowork, released for Mac in January 2026 and for Windows in February 2026, is an AI agent developed by Anthropic that can autonomously execute file operations and browser actions on a PC based on natural-language instructions. It has attracted attention as a tool that allows even non-engineers to automate complex workflows.
Claude Cowork is particularly strong in work domains that require careful reading, analysis, and cautious document drafting. Unlike tools such as ChatGPT, which excel at brainstorming and general task processing, Claude Cowork is considered highly compatible with legal and intellectual property work, where accuracy and conservative judgment are critical—such as contract review and regulatory compliance.
In intellectual property operations, it can potentially be used across a wide range of tasks, including organizing and analyzing patent portfolios, investigating competitors’ patent trends, reviewing license agreements, and supporting communication with specialists such as patent attorneys.
However, because the system can access local files on a user’s computer, special care must be taken in handling confidential information.
This report further explores the possible applications of Claude Cowork in intellectual property work using generative AI. Please note that the research and analysis produced by generative AI are based solely on publicly available information and may not necessarily reflect actual circumstances. The results may also contain inaccuracies, so they should be referenced with appropriate caution.
 

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「Claude Cowork」でAIと"一緒に働く

15/3/2026

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2026年3月14日に高裁されたプレジデントオンラインアカデミーの『【無料公開】池田朋弘 AI知識のアプデ【最新の生成AIサービス①】「Claude Cowork」でAIと"一緒に働く"時代が来た!?』が「Claude Cowork」を分かりやすく説明していました。
動画を観てもらうのが一番良いのですが、時間がない方のために、NotebookLM(レポート、インフォグラフィック、スライド資料)で紹介します。
 
【無料公開】池田朋弘 AI知識のアプデ【最新の生成AIサービス①】「Claude Cowork」でAIと"一緒に働く"時代が来た!?
https://www.youtube.com/watch?v=pa7mQR71TRw
 
 
Working with AI through “Claude Cowork”
A lecture titled “[Free Release] Tomohiro Ikeda: AI Knowledge Update [Latest Generative AI Services #1] – The Era of Working with AI through ‘Claude Cowork’ Has Arrived!?”, published on March 14, 2026 on the President Online Academy, provides a clear and accessible explanation of Claude Cowork.
The best way to understand it is to watch the video itself, but for those who do not have the time, I will introduce the key points using materials generated with NotebookLM (report, infographic, and slide materials).

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マイクロソフトがAnthropicと提携した「Copilot Cowork」

14/3/2026

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2026年3月9日、マイクロソフトは自社のAIアシスタント「Microsoft 365 Copilot」に、Anthropicとの提携により開発した自律型AI機能「Copilot Cowork」を導入すると発表しました。
本件について、生成に深堀させました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
マイクロソフト、自律型AI機能「Copilot Cowork」発表 Anthropicと提携
https://japan.cnet.com/article/35244807/?tag=nl
 
 
Microsoft Announces “Copilot Cowork” Developed in Partnership with Anthropic
On March 9, 2026, Microsoft announced that it will introduce an autonomous AI capability called “Copilot Cowork” into its AI assistant Microsoft 365 Copilot, developed through a partnership with Anthropic.
I asked a generative AI system to conduct a deeper analysis of this development. Please note that the investigation and analysis produced by generative AI are based solely on publicly available information. They do not necessarily reflect the actual situation and may contain inaccuracies. Please keep this in mind when reviewing the information.

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「AI事業者ガイドライン」改訂がAI利用者に及ぼす影響

14/3/2026

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2026年3月末に予定されている「AI事業者ガイドライン」の改訂は、AIを開発・提供する事業者だけでなく、業務で生成AIを「利用」する企業にも重大な影響を及ぼします。
今回の改訂は、生成AIや自律的にタスクを遂行する「AIエージェント」の急速な普及と、それに伴う新たなリスクの顕在化に対応するものです。
単なるAI利用企業であっても、従業員の個人的な利用(シャドーIT)を含め、組織としての管理責任が問われる時代に突入しています。万が一、著作権侵害や情報漏洩が発生した場合、その責任はAI開発会社ではなく、AIを利用した企業自身が負うのが原則です。
このため、利用企業には、法的・倫理的リスクを管理し、AIを安全かつ効果的に活用するための「AIガバナンス」体制の構築が急務となります。その中核となるのが、実効性のある「社内ガイドライン」の策定と運用です。これは単なる「禁止リスト」ではなく、従業員が安心してAIの恩恵を享受するための「交通ルール」と位置づけ、利用目的の明確化、許諾ツールの指定、入力禁止情報の定義、生成物の確認プロセスなどを具体的に定める必要があります。
この2026年の「AI事業者ガイドライン」改訂が、自社でAIモデルを開発しない「単なるAI利用者(会社)」に対してどのような影響を及ぼすのかをついて、生成AIに深掘りさせました。
なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
 
Impact of the Revision of the “AI Business Operator Guidelines” on AI Users
The revision of the “AI Business Operator Guidelines” scheduled for the end of March 2026 will have significant implications not only for companies that develop or provide AI, but also for companies that use generative AI in their business operations.
This revision responds to the rapid spread of generative AI and AI agents capable of autonomously performing tasks, as well as the emergence of new risks associated with these technologies.
Even companies that merely use AI are entering an era in which organizational management responsibility is questioned, including cases involving employees’ personal use of AI tools (so-called shadow IT). If problems such as copyright infringement or information leakage occur, the responsibility will, in principle, fall not on the AI developer but on the company that used the AI.
For this reason, companies that use AI must urgently establish AI governance frameworks to manage legal and ethical risks while enabling the safe and effective use of AI. At the core of such governance is the development and operation of effective internal AI guidelines.
These guidelines should not merely function as a “list of prohibitions.” Instead, they should serve as “traffic rules” that allow employees to benefit from AI with confidence. They need to clearly define elements such as:
  • the purpose of AI use,
  • approved AI tools,
  • types of information that must not be input, and
  • processes for reviewing AI-generated outputs.
In this analysis, generative AI was used to conduct a deeper examination of how the 2026 revision of the “AI Business Operator Guidelines” will affect companies that do not develop their own AI models and are simply AI users.
Please note that the research and analysis conducted by generative AI are based solely on publicly available information, and therefore may not fully reflect actual circumstances and may contain inaccuracies. Please review the content with this understanding.

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三井化学が化学構造式のAIによる読み取りを可能に

13/3/2026

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三井化学が、学術文献や研究報告書に記載された化学構造式から化合物に関する情報を自律的に調査・整理する生成AIエージェントシステムを独自に開発し、社内での実証実験を開始しました。初期検証において、研究者の文献調査時間を80%以上削減できることを確認できたことから2025年度内に実証実験を完了し、2026年度からの本格運用を目指すということです。
この記事について、生成AIに深掘りさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
三井化学、研究開発の文献調査を革新する生成Alエージェントを開発
~化学構造式から化合物情報を自律抽出、文献調査時間を80%以上削減~
2026.03.02
https://jp.mitsuichemicals.com/jp/release/2026/2026_0302/index.htm
 
2026-03-03
三井化学、化学構造式から化合物を自律抽出する生成AIエージェントを開発し文献調査時間を80%以上削減へ
https://iotnews.jp/ai/272026/
 
 
Mitsui Chemicals Enables AI-Based Interpretation of Chemical Structural Formulas
Mitsui Chemicals has independently developed a generative AI agent system capable of autonomously investigating and organizing information about compounds based on chemical structural formulas described in academic papers and research reports. The company has begun internal proof-of-concept experiments using this system.
In the initial verification, it was confirmed that the system can reduce researchers’ literature review time by more than 80%. Based on these results, Mitsui Chemicals plans to complete the proof-of-concept experiments within fiscal year 2025 and aims to begin full-scale operation from fiscal year 2026.
I asked generative AI to conduct a deeper analysis of this development. Please note that the analysis produced by generative AI is based solely on publicly available information and may not necessarily reflect the actual situation. It may also contain inaccuracies, so please refer to it with this understanding.
 
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日本成長戦略会議ロードマップにおける重大な構造的課題

12/3/2026

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2026年3月10日に開催された第3回日本成長戦略会議で示された17戦略分野・61製品技術の官民投資ロードマップは、知的財産の観点から見ると重大な構造的課題を抱えています。日本のAI特許の国際競争力は中国の10分の1以下、若手弁理士は10年で55%減少など、戦略分野を支えるIP基盤が脆弱化しているのが実情です。
これらの点について、生成Aini深掘りさせました。さらに、結果をNotebookLMでインフォグラフィック、スライド資料にさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
Major Structural Challenges in the Roadmap of the Japan Growth Strategy Council
From the perspective of intellectual property, the public–private investment roadmap covering 17 strategic sectors and 61 product technologies, presented at the 3rd Japan Growth Strategy Council held on March 10, 2026, faces significant structural challenges. In reality, the IP foundation supporting these strategic fields is weakening—for example, the international competitiveness of Japan’s AI patents is less than one-tenth of China’s, and the number of young patent attorneys has declined by 55% over the past decade.
I asked generative AI to conduct an in-depth analysis of these issues. The results were then converted into infographics and presentation slides using NotebookLM.
Please note that the research and analysis generated by AI are based solely on publicly available information and may not necessarily reflect the actual situation; they may also contain inaccuracies. Please keep this in mind when referring to the material.
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日本成長戦略会議に対する国内外の評価

12/3/2026

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2026年3月10日、日本政府は「日本成長戦略会議」を開催し、高市早苗政権の経済政策の根幹を成す包括的な投資ロードマップと成長戦略の骨子を決定しました。この会議は、従来の均衡財政主義からの決別を象徴するものであり、国家安全保障と経済成長を不可分なものとして捉える「危機管理投資」という新たなパラダイムを提示しました。
生成AIに、この「日本成長戦略会議」における決定事項の戦略的意義、国内外の市場・専門家による評価、民間セクターの反応などについて、多角的な視点から詳細に分析させました。さらに、結果をNotebookLMでインフォグラフィック、スライド資料にさせました。なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。
 
日本成長戦略会議
https://www.kantei.go.jp/jp/105/actions/202603/10seichyou.html
 
 
Domestic and International Evaluations of the Japan Growth Strategy Conference
On March 10, 2026, the Japanese government convened the “Japan Growth Strategy Conference” and decided on the outline of a comprehensive investment roadmap and growth strategy that forms the core of the economic policy of the Sanae Takaichi administration. This conference symbolized a departure from the conventional balanced‑budget doctrine and presented a new paradigm of “crisis‑management investment,” which views national security and economic growth as inseparable.
Generative AI was used to conduct a detailed, multi‑perspective analysis of the strategic significance of the decisions made at this Japan Growth Strategy Conference, as well as the evaluations by domestic and international markets and experts, and the reactions of the private sector. Furthermore, the results were converted into infographics and slide materials using NotebookLM.
Please note that the research and analysis conducted by generative AI are based solely on publicly available information and may not necessarily reflect the actual situation. The analysis may also contain incorrect information, so please keep this in mind when referring to it.

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